Call the logits probs in create_inference_graph
after they go thru softmax
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@ -730,7 +730,7 @@ def create_inference_graph(batch_size=1, n_steps=16, tflite=False):
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logits = tf.squeeze(logits, [1])
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# Apply softmax for CTC decoder
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logits = tf.nn.softmax(logits, name='logits')
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probs = tf.nn.softmax(logits, name='logits')
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if batch_size <= 0:
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if tflite:
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@ -743,7 +743,7 @@ def create_inference_graph(batch_size=1, n_steps=16, tflite=False):
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'input_lengths': seq_length,
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},
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{
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'outputs': logits,
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'outputs': probs,
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},
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layers
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)
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@ -763,7 +763,7 @@ def create_inference_graph(batch_size=1, n_steps=16, tflite=False):
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inputs['input_lengths'] = seq_length
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outputs = {
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'outputs': logits,
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'outputs': probs,
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'new_state_c': new_state_c,
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'new_state_h': new_state_h,
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'mfccs': mfccs,
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